Search results for: Cluster formation.
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1139

Search results for: Cluster formation.

989 Clustering Multivariate Empiric Characteristic Functions for Multi-Class SVM Classification

Authors: María-Dolores Cubiles-de-la-Vega, Rafael Pino-Mejías, Esther-Lydia Silva-Ramírez

Abstract:

A dissimilarity measure between the empiric characteristic functions of the subsamples associated to the different classes in a multivariate data set is proposed. This measure can be efficiently computed, and it depends on all the cases of each class. It may be used to find groups of similar classes, which could be joined for further analysis, or it could be employed to perform an agglomerative hierarchical cluster analysis of the set of classes. The final tree can serve to build a family of binary classification models, offering an alternative approach to the multi-class SVM problem. We have tested this dendrogram based SVM approach with the oneagainst- one SVM approach over four publicly available data sets, three of them being microarray data. Both performances have been found equivalent, but the first solution requires a smaller number of binary SVM models.

Keywords: Cluster Analysis, Empiric Characteristic Function, Multi-class SVM, R.

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988 Discovering Complex Regularities by Adaptive Self Organizing Classification

Authors: A. Faro, D. Giordano, F. Maiorana

Abstract:

Data mining uses a variety of techniques each of which is useful for some particular task. It is important to have a deep understanding of each technique and be able to perform sophisticated analysis. In this article we describe a tool built to simulate a variation of the Kohonen network to perform unsupervised clustering and support the entire data mining process up to results visualization. A graphical representation helps the user to find out a strategy to optmize classification by adding, moving or delete a neuron in order to change the number of classes. The tool is also able to automatically suggest a strategy for number of classes optimization.The tool is used to classify macroeconomic data that report the most developed countries? import and export. It is possible to classify the countries based on their economic behaviour and use an ad hoc tool to characterize the commercial behaviour of a country in a selected class from the analysis of positive and negative features that contribute to classes formation.

Keywords: Unsupervised classification, Kohonen networks, macroeconomics, Visual data mining, cluster interpretation.

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987 Stock Characteristics and Herding Formation: Evidence from the United States Equity Market

Authors: Chih-Hsiang Chang, Fang-Jyun Su

Abstract:

This paper explores whether stock characteristics influence the herding formation among investors in the US equity market. To extend the research scope of the existing literature, this paper further examines the role that stock risk characteristics play in the US equity market, and the way they influence investors’ decision-making. First, empirical results show that whether general stocks or high-risk stocks, there are no herding behaviors among the investors in the US equity market during the whole research period or during four great events. Moreover, stock characteristics have great influence on investors’ trading decisions. Finally, there is a bidirectional lead-lag relationship of the herding formation between high-risk stocks and low-risk stocks, but the influence of high-risk stocks on the low-risk stocks is stronger than that of low-risk stocks on the high-risk stocks.

Keywords: Stock characteristics, herding formation, investment decision, US equity market, lead-lag relationship.

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986 The Role of Knowledge Management in Innovation: Spanish Evidence

Authors: María Jesús Luengo-Valderrey, Mónica Moso-Díez

Abstract:

In the knowledge-based economy, innovation is considered essential in order to achieve survival and growth in organizations. On the other hand, knowledge management is currently understood as one of the keys to innovation process. Both factors are generally admitted as generators of competitive advantage in organizations. Specifically, activities on R&D&I and those that generate internal knowledge have a positive influence in innovation results. This paper examines this effect and if it is similar or not is what we aimed to quantify in this paper. We focus on the impact that proportion of knowledge workers, the R&D&I investment, the amounts destined for ICTs and training for innovation have on the variation of tangible and intangibles returns for the sector of high and medium technology in Spain. To do this, we have performed an empirical analysis on the results of questionnaires about innovation in enterprises in Spain, collected by the National Statistics Institute. First, using clusters methodology, the behavior of these enterprises regarding knowledge management is identified. Then, using SEM methodology, we performed, for each cluster, the study about cause-effect relationships among constructs defined through variables, setting its type and quantification. The cluster analysis results in four groups in which cluster number 1 and 3 presents the best performance in innovation with differentiating nuances among them, while clusters 2 and 4 obtained divergent results to a similar innovative effort. However, the results of SEM analysis for each cluster show that, in all cases, knowledge workers are those that affect innovation performance most, regardless of the level of investment, and that there is a strong correlation between knowledge workers and investment in knowledge generation. The main findings reached is that Spanish high and medium technology companies improve their innovation performance investing in internal knowledge generation measures, specially, in terms of R&D activities, and underinvest in external ones. This, and the strong correlation between knowledge workers and the set of activities that promote the knowledge generation, should be taken into account by managers of companies, when making decisions about their investments for innovation, since they are key for improving their opportunities in the global market.

Keywords: High and medium technology sector, innovation, knowledge management, Spanish companies.

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985 Preliminary Geotechnical Properties of Uncemented Sandstone Kati Formation

Authors: Nursyafiqah Abdul Kahar, Niraku Rosmawati Ahmad, Hisham Mohamad, Siti Nuruljannah Mohd Marzuki

Abstract:

Assessment of geotechnical properties of the subsoil is necessary for generating relevant input for the design and construction of a foundation. It is significant for the future development in the area. The focus of this research is to investigate the preliminary geotechnical properties of the uncemented sandstone from Kati formation at Puncak Iskandar, Seri Iskandar. A series of basic soil tests, oedometer and direct shear box tests were carried out to obtain the soil parameters. The uncemented sandstone of Kati Formation was found to have well-graded and poorly graded sand distribution, depending on the location where the samples were obtained. The sand grains distribution was in a range of 82%-100% while, the specific gravity of the uncemented sandstone is in the range 2.65-2.86. The preconsolidation pressure for USB3 was 990 kPa indicating that the sandstone at USB3 sample had undergone 990 kPa of overburden pressure. The angle of friction for uncemented sandstone was ranging between 23.34°-32.92°.

Keywords: Geotechnical properties, Kati formation, uncemented sandstone, oedometer test, shear box test.

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984 An Adaptive Fuzzy Clustering Approach for the Network Management

Authors: Amal Elmzabi, Mostafa Bellafkih, Mohammed Ramdani

Abstract:

The Chiu-s method which generates a Takagi-Sugeno Fuzzy Inference System (FIS) is a method of fuzzy rules extraction. The rules output is a linear function of inputs. In addition, these rules are not explicit for the expert. In this paper, we develop a method which generates Mamdani FIS, where the rules output is fuzzy. The method proceeds in two steps: first, it uses the subtractive clustering principle to estimate both the number of clusters and the initial locations of a cluster centers. Each obtained cluster corresponds to a Mamdani fuzzy rule. Then, it optimizes the fuzzy model parameters by applying a genetic algorithm. This method is illustrated on a traffic network management application. We suggest also a Mamdani fuzzy rules generation method, where the expert wants to classify the output variables in some fuzzy predefined classes.

Keywords: Fuzzy entropy, fuzzy inference systems, genetic algorithms, network management, subtractive clustering.

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983 Fault Detection and Isolation in Attitude Control Subsystem of Spacecraft Formation Flying Using Extended Kalman Filters

Authors: S. Ghasemi, K. Khorasani

Abstract:

In this paper, the problem of fault detection and isolation in the attitude control subsystem of spacecraft formation flying is considered. In order to design the fault detection method, an extended Kalman filter is utilized which is a nonlinear stochastic state estimation method. Three fault detection architectures, namely, centralized, decentralized, and semi-decentralized are designed based on the extended Kalman filters. Moreover, the residual generation and threshold selection techniques are proposed for these architectures.

Keywords: Formation flight of satellites, extended Kalman filter, fault detection and isolation, actuator fault.

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982 Liver Lesion Extraction with Fuzzy Thresholding in Contrast Enhanced Ultrasound Images

Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

Abstract:

In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: Defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets.

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981 Geology, Geomorphology and Genesis of Andarokh Karstic Cave, North-East Iran

Authors: Mojtaba Heydarizad

Abstract:

Andarokh basin is one of the main karstic regions in Khorasan Razavi province NE Iran. This basin is part of Kopeh-Dagh mega zone extending from Caspian Sea in the east to northern Afghanistan in the west. This basin is covered by Mozdooran Formation, Ngr evaporative formation and quaternary alluvium deposits in descending order of age. Mozdooran carbonate formation is notably karstified. The main surface karstic features in Mozdooran formation are Groove karren, Cleft karren, Rain pit, Rill karren, Tritt karren, Kamintza, Domes, and Table karren. In addition to surface features, deep karstic feature Andarokh Cave also exists in the region. Studying Ca, Mg, Mn, Sr, Fe concentration and Sr/Mn ratio in Mozdooran formation samples with distance to main faults and joints system using PCA analyses demonstrates intense meteoric digenesis role in controlling carbonate rock geochemistry. The karst evaluation in Andarokh basin varies from early stages 'deep seated karst' in Mesozoic to mature karstic system 'Exhumed karst' in quaternary period. Andarokh cave (the main cave in Andarokh basin) is rudimentary branch work consists of three passages of A, B and C and two entrances Andarokh and Sky.

Keywords: Andarokh basin, Andarokh cave, geochemical analyses and karst evaluation.

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980 Phase Formation of Ba(Ce1-xZrx)0.90Y0.1O3-δ Prepared by a Modified Sol-Gel Method

Authors: N. Z. Baderisham, H. A. Hamid, N. Osman

Abstract:

The powders of Ba(Ce1-xZrx)0.90Y0.1O3-δ (BCZY) with 0.2 ≤ x ≤ 0.6 have been prepared by a modified sol-gel method. Triethylenetetramine (TETA) was employed as chelating agent. Phase formation of calcined powders at 1100oC and sintered pellets at 1400oC of BCZY were examined by an X-ray diffractrometer (XRD). XRD results showed the calcined powder and sintered pellet formed a single perovskite phase over the entire range of x values. As the amount of zirconium substitution (x values) increase, the main peaks are shifted to the higher 2theta values which suggest a complete substitution of zirconium into cerium sites. All the obtained calcined powders and sintered pellets possess cubic structure (Pm-3m) at all x values.

Keywords: Structure, phase formation, modified sol-gel, cerate-zirconate electrolye, XRD.

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979 Multi-Agent Systems for Intelligent Clustering

Authors: Jung-Eun Park, Kyung-Whan Oh

Abstract:

Intelligent systems are required in order to quickly and accurately analyze enormous quantities of data in the Internet environment. In intelligent systems, information extracting processes can be divided into supervised learning and unsupervised learning. This paper investigates intelligent clustering by unsupervised learning. Intelligent clustering is the clustering system which determines the clustering model for data analysis and evaluates results by itself. This system can make a clustering model more rapidly, objectively and accurately than an analyzer. The methodology for the automatic clustering intelligent system is a multi-agent system that comprises a clustering agent and a cluster performance evaluation agent. An agent exchanges information about clusters with another agent and the system determines the optimal cluster number through this information. Experiments using data sets in the UCI Machine Repository are performed in order to prove the validity of the system.

Keywords: Intelligent Clustering, Multi-Agent System, PCA, SOM, VC(Variance Criterion)

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978 An Agent Based Simulation for Network Formation with Heterogeneous Agents

Authors: Hisashi Kojima, Masatora Daito

Abstract:

We investigate an asymmetric connections model with a dynamic network formation process, using an agent based simulation. We permit heterogeneity of agents- value. Valuable persons seem to have many links on real social networks. We focus on this point of view, and examine whether valuable agents change the structures of the terminal networks. Simulation reveals that valuable agents diversify the terminal networks. We can not find evidence that valuable agents increase the possibility that star networks survive the dynamic process. We find that valuable agents disperse the degrees of agents in each terminal network on an average.

Keywords: network formation, agent based simulation, connections model.

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977 Effect of Retinoic Acid on Fetus Reproductive Organ Mice (Mus musculus) Swiss Webster

Authors: Yulia Irnidayanti

Abstract:

Retinoic acid is like a steroid hormone that plays a role in embryo formation, proliferation of spermatogonia cells, ephitelial cells differentiation and organogenesis. Retinoic acid can influences seminiferous tubule formation during embryonic testis development and also play a role in the regulation of ovarian function and female reproductive tract by suppressing the hormones FSH receptor expression. The excessive use of retinoic acid caused abnormalities in the fetus. The result showed that there is the influence of retinoic acid on the developmet of mice fetal testes, for examples disruption of the formation of seminiferous tubules and tubules seemed to be hollow, spermatogonia cells are relatively few in number and caused Leydig cells count relatively more. While in the female fetus does not caused the formation of primordial follicles and disrupted the development of germinal ephitelial cells of fetal ovaries of female mice (mus musculus) Swiss Webster.

Keywords: Retinoic acid, Leydig cell, Spermatogonia cells, Semin- ferous tubules, Primordial follicles

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976 Nugget Formation during Resistance Spot Welding using Finite Element Model

Authors: Jawad Saleem, Abdul Majid, Kent Bertilsson, Torbjörn Carlberg, Nazar Ul Islam

Abstract:

Resistance spot welding process comprises of electric, thermal and mechanical phenomenon, which makes this process complex and highly non-linear and thus, it becomes difficult to model it. In order to obtain good weld nugget during spot welding, hit and trial welds are usually done which is very costly. Therefore the numerical simulation research has been conducted to understand the whole process. In this paper three different cases were analyzed by varying the tip contact area and it was observed that, with the variation of tip contact area the nugget formation at the faying surface is affected. The tip contact area of the welding electrode becomes large with long welding cycles. Therefore in order to maintain consistency of nugget formation during the welding process, the current compensation in control feedback is required. If the contact area of the welding electrode tip is reduced, a large amount of current flows through the faying surface, as a result of which sputtering occurs.

Keywords: Resistance spot welding, Finite element modeling, Nugget formation, Welding electrode, Numerical method simulation,

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975 South Africa’s Industrial Expansion – The Role of Technology Transfer

Authors: Charles Mbohwa, Gift Nyambe

Abstract:

The paper reviews South Africa’s industrialization, the basis of its formation and to establish whether it can be expanded using technology transfer mechanisms principles. It also seek to draw comparisons from other industrialized countries and as a baseline, and take lessons on how these industrialized countries have achieved their secondary industrialization; hence they are known as the developed countries. It identifies the challenges faced by South Africa’s current industrial base and recommend ways that could be meaningful in assisting it to be expandable. It also seeks to contribute to the existing body of knowledge on industrialization and technology transfer in advancing industry formation. It is also the intention of the paper to look at best principles outlined in operations management theories on how they could be of value in strengthening industrial formation and expansion. These principles include but not limited to the application of lean manufacturing principles, however they are not only applicable to the manufacturing sector but to any business optimization strategy. There will be emphasize on the role of the primary sector in South Africa’s industrialization and the opportunities it ought to bring in strengthening and harnessing the success of the secondary sector formation.

Keywords: Industrialization, Expansion, operations and Technology transfer.

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974 Features of Soil Formation in the North of Western Siberia in Cryogenic Conditions

Authors: Tatiana V. Raudina, Sergey P. Kulizhskiy

Abstract:

A large part of Russia is located in permafrost areas. These areas are widely used because there are concentrated valuable natural resources. Therefore to explore of cryosols it is important due to the significant increase of anthropogenic stress as well as the problem of global climate change. In the north of Western Siberia permafrost phenomena is widespread. Permafrost as a factor of soil formation and cryogenesis as a process have a great impact on the soil formation of these areas. Based on the research results of permafrost-affected soils tundra landscapes formed in the central part of the Tazovskiy Peninsula in cryogenic conditions, data were obtained which characterize the morphological features of soils. The specificity of soil cover distribution and manifestation of soil-forming processes within the study area are noted. Permafrost features such as frost cracking, cryoturbation, thixotropy, movement of humus are formed. The formation of these features is increased with the development of the territory. As a consequence, there is a change in the components of the environment and the destruction of the soil cover.

Keywords: Gleyed and nongleyed soils, permafrost, soil cryogenesis (pedocryogenesis), soil-forming macroprocesses.

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973 A Software of Intrusion Detection Mechanism for Virtual Platforms

Authors: Ying-Chuan Chen, Shuen-Tai Wang

Abstract:

Security is an interesting and significance issue for popular virtual platforms, such as virtualization cluster and cloud platforms. Virtualization is the powerful technology for cloud computing services, there are a lot of benefits by using virtual machine tools which be called hypervisors, such as it can quickly deploy all kinds of virtual Operating Systems in single platform, able to control all virtual system resources effectively, cost down for system platform deployment, ability of customization, high elasticity and high reliability. However, some important security problems need to take care and resolved in virtual platforms that include terrible viruses, evil programs, illegal operations and intrusion behavior. In this paper, we present useful Intrusion Detection Mechanism (IDM) software that not only can auto to analyze all system-s operations with the accounting journal database, but also is able to monitor the system-s state for virtual platforms.

Keywords: security, cluster, cloud, virtualization, virtual machine, virus, intrusion detection

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972 Simultaneous Clustering and Feature Selection Method for Gene Expression Data

Authors: T. Chandrasekhar, K. Thangavel, E. N. Sathishkumar

Abstract:

Microarrays are made it possible to simultaneously monitor the expression profiles of thousands of genes under various experimental conditions. It is used to identify the co-expressed genes in specific cells or tissues that are actively used to make proteins. This method is used to analysis the gene expression, an important task in bioinformatics research. Cluster analysis of gene expression data has proved to be a useful tool for identifying co-expressed genes, biologically relevant groupings of genes and samples. In this work K-Means algorithms has been applied for clustering of Gene Expression Data. Further, rough set based Quick reduct algorithm has been applied for each cluster in order to select the most similar genes having high correlation. Then the ACV measure is used to evaluate the refined clusters and classification is used to evaluate the proposed method. They could identify compact clusters with feature selection method used to genes are selected.

Keywords: Clustering, Feature selection, Gene expression data, Quick reduct.

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971 Clustering Protein Sequences with Tailored General Regression Model Technique

Authors: G. Lavanya Devi, Allam Appa Rao, A. Damodaram, GR Sridhar, G. Jaya Suma

Abstract:

Cluster analysis divides data into groups that are meaningful, useful, or both. Analysis of biological data is creating a new generation of epidemiologic, prognostic, diagnostic and treatment modalities. Clustering of protein sequences is one of the current research topics in the field of computer science. Linear relation is valuable in rule discovery for a given data, such as if value X goes up 1, value Y will go down 3", etc. The classical linear regression models the linear relation of two sequences perfectly. However, if we need to cluster a large repository of protein sequences into groups where sequences have strong linear relationship with each other, it is prohibitively expensive to compare sequences one by one. In this paper, we propose a new technique named General Regression Model Technique Clustering Algorithm (GRMTCA) to benignly handle the problem of linear sequences clustering. GRMT gives a measure, GR*, to tell the degree of linearity of multiple sequences without having to compare each pair of them.

Keywords: Clustering, General Regression Model, Protein Sequences, Similarity Measure.

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970 Atomic Clusters: A Unique Building Motif for Future Smart Nanomaterials

Authors: Debesh R. Roy

Abstract:

The fundamental issue in understanding the origin and growth mechanism of nanomaterials, from a fundamental unit is a big challenging problem to the scientists. Recently, an immense attention is generated to the researchers for prediction of exceptionally stable atomic cluster units as the building units for future smart materials. The present study is a systematic investigation on the stability and electronic properties of a series of bimetallic (semiconductor-alkaline earth) clusters, viz., BxMg3 (x=1-5) is performed, in search for exceptional and/ or unusual stable motifs. A very popular hybrid exchange-correlation functional, B3LYP along with a higher basis set, viz., 6-31+G[d,p] is employed for this purpose under the density functional formalism. The magic stability among the concerned clusters is explained using the jellium model. It is evident from the present study that the magic stability of B4Mg3 cluster arises due to the jellium shell closure.

Keywords: Atomic Clusters, Density Functional Theory, Jellium Model, Magic Clusters, Smart Nanomaterials.

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969 Fuzzy Clustering of Locations for Degree of Accident Proneness based on Vehicle User Perceptions

Authors: Jayanth Jacob, C. V. Hariharakrishnan, Suganthi L.

Abstract:

The rapid urbanization of cities has a bane in the form road accidents that cause extensive damage to life and limbs. A number of location based factors are enablers of road accidents in the city. The speed of travel of vehicles is non-uniform among locations within a city. In this study, the perception of vehicle users is captured on a 10-point rating scale regarding the degree of variation in speed of travel at chosen locations in the city. The average rating is used to cluster locations using fuzzy c-means clustering and classify them as low, moderate and high speed of travel locations. The high speed of travel locations can be classified proactively to ensure that accidents do not occur due to the speeding of vehicles at such locations. The advantage of fuzzy c-means clustering is that a location may be a part of more than one cluster to a varying degree and this gives a better picture about the location with respect to the characteristic (speed of travel) being studied.

Keywords: C-means clustering, Location Specific, Road Accidents.

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968 Forest Growth Simulation: Tropical Rain Forest Stand Table Projection

Authors: Yasmin Yahya, Roslan Ismail, Samreth Vanna, Khorn Saret

Abstract:

The study on the tree growth for four species groups of commercial timber in Koh Kong province, Cambodia-s tropical rainforest is described. The simulation for these four groups had been successfully developed in the 5-year interval through year-60. Data were obtained from twenty permanent sample plots in the duration of thirteen years. The aim for this study was to develop stand table simulation system of tree growth by the species group. There were five steps involved in the development of the tree growth simulation: aggregate the tree species into meaningful groups by using cluster analysis; allocate the trees in the diameter classes by the species group; observe the diameter movement of the species group. The diameter growth rate, mortality rate and recruitment rate were calculated by using some mathematical formula. Simulation equation had been created by combining those parameters. Result showed the dissimilarity of the diameter growth among species groups.

Keywords: cluster analysis, diameter growth, simulation

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967 Solar-Inducted Cluster Head Relocation Algorithm

Authors: Goran Djukanovic, Goran Popovic

Abstract:

A special area in the study of Wireless Sensor Networks (WSNs) is how to move sensor nodes, as it expands the scope of application of wireless sensors and provides new opportunities to improve network performance. On the other side, it opens a set of new problems, especially if complete clusters are mobile. Node mobility can prolong the network lifetime. In such WSN, some nodes are possibly moveable or nomadic (relocated periodically), while others are static. This paper presents an idea of mobile, solar-powered CHs that relocate themselves inside clusters in such a way that the total energy consumption in the network reduces, and the lifetime of the network extends. Positioning of CHs is made in each round based on selfish herd hypothesis, where leader retreats to the center of gravity. Based on this idea, an algorithm, together with its modified version, has been presented and tested in this paper. Simulation results show that both algorithms have benefits in network lifetime, and prolongation of network stability period duration.

Keywords: CH-active algorithm, mobile cluster head, sensors, wireless sensor network.

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966 One-Class Support Vector Machines for Aerial Images Segmentation

Authors: Chih-Hung Wu, Chih-Chin Lai, Chun-Yen Chen, Yan-He Chen

Abstract:

Interpretation of aerial images is an important task in various applications. Image segmentation can be viewed as the essential step for extracting information from aerial images. Among many developed segmentation methods, the technique of clustering has been extensively investigated and used. However, determining the number of clusters in an image is inherently a difficult problem, especially when a priori information on the aerial image is unavailable. This study proposes a support vector machine approach for clustering aerial images. Three cluster validity indices, distance-based index, Davies-Bouldin index, and Xie-Beni index, are utilized as quantitative measures of the quality of clustering results. Comparisons on the effectiveness of these indices and various parameters settings on the proposed methods are conducted. Experimental results are provided to illustrate the feasibility of the proposed approach.

Keywords: Aerial imaging, image segmentation, machine learning, support vector machine, cluster validity index

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965 Study of Asphaltene Precipitation İnduced Formation Damage During CO2 Injection for a Malaysian Light Oil

Authors: Sima Sh. Alian, Abdul Aziz Omar, Ali F. Alta'ee, Irzie Hani

Abstract:

In this work, the precipitation of asphaltene from a Malaysian light oil reservoir was studies. A series of experiments were designed and carried out to examine the effect of CO2 injection on asphaltene precipitation. Different pressures of injections were used in Dynamic flooding experiment in order to investigate the effect of pressure versus injection pore volume of CO2. These dynamic displacement tests simulate reservoir condition. Results show that by increasing the pore volume of injected gas asphaltene precipitation will increases, also rise in injection pressure causes less precipitation. Sandstone core plug was used to represent reservoir formation during displacement test; therefore it made it possible to study the effect of present of asphaltene on formation. It is found out that the precipitated asphaltene can reduce permeability and porosity which is not favorable during oil production.

Keywords: Asphaltene, asphaltene precipitation, enhanced oil recovery.

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964 A Design for Customer Preferences Model by Cluster Analysis of Geometric Features and Customer Preferences

Authors: Yuan-Jye Tseng, Ching-Yen Chen

Abstract:

In the design cycle, a main design task is to determine the external shape of the product. The external shape of a product is one of the key factors that can affect the customers’ preferences linking to the motivation to buy the product, especially in the case of a consumer electronic product such as a mobile phone. The relationship between the external shape and the customer preferences needs to be studied to enhance the customer’s purchase desire and action. In this research, a design for customer preferences model is developed for investigating the relationships between the external shape and the customer preferences of a product. In the first stage, the names of the geometric features are collected and evaluated from the data of the specified internet web pages using the developed text miner. The key geometric features can be determined if the number of occurrence on the web pages is relatively high. For each key geometric feature, the numerical values are explored using the text miner to collect the internet data from the web pages. In the second stage, a cluster analysis model is developed to evaluate the numerical values of the key geometric features to divide the external shapes into several groups. Several design suggestion cases can be proposed, for example, large model, mid-size model, and mini model, for designing a mobile phone. A customer preference index is developed by evaluating the numerical data of each of the key geometric features of the design suggestion cases. The design suggestion case with the top ranking of the customer preference index can be selected as the final design of the product. In this paper, an example product of a notebook computer is illustrated. It shows that the external shape of a product can be used to drive customer preferences. The presented design for customer preferences model is useful for determining a suitable external shape of the product to increase customer preferences.

Keywords: Cluster analysis, customer preferences, design evaluation, design for customer preferences, product design.

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963 Low resistivity Hf/Al/Ni/Au Ohmic Contact Scheme to n-Type GaN

Authors: Y. Liu, M. K. Bera, L. M. Kyaw, G. Q. Lo, E. F. Chor

Abstract:

The electrical and structural properties of Hf/Al/Ni/Au (20/100/25/50 nm) ohmic contact to n-GaN are reported in this study. Specific contact resistivities of Hf/Al/Ni/Au based contacts have been investigated as a function of annealing temperature and achieve the lowest value of 1.09´10-6 Ω·cm2 after annealing at 650 oC in vacuum. A detailed mechanism of ohmic contact formation is discussed. By using different chemical analyses, it is anticipated that the formation of Hf-Al-N alloy might be responsible to form low temperature ohmic contacts for the Hf-based scheme to n-GaN.

Keywords: Gallium nitride, ohmic contact, Hafnium

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962 An E-Assessment Website to Implement Hierarchical Aggregate Assessment

Authors: M. Lesage, G. Raîche, M. Riopel, F. Fortin, D. Sebkhi

Abstract:

This paper describes a Web server implementation of the hierarchical aggregate assessment process in the field of education. This process describes itself as a field of teamwork assessment where teams can have multiple levels of hierarchy and supervision. This process is applied everywhere and is part of the management, education, assessment and computer science fields. The E-Assessment website named “Cluster” records in its database the students, the course material, the teams and the hierarchical relationships between the students. For the present research, the hierarchical relationships are team member, team leader and group administrator appointments. The group administrators have the responsibility to supervise team leaders. The experimentation of the application has been performed by high school students in geology courses and Canadian army cadets for navigation patrols in teams. This research extends the work of Nance that uses a hierarchical aggregation process similar as the one implemented in the “Cluster” application. 

Keywords: E-Learning, E-Assessment, Teamwork Assessment, Hierarchical Aggregate Assessment.

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961 Energy Efficient Cooperative Caching in WSN

Authors: Narottam Chand

Abstract:

Wireless sensor networks (WSNs) consist of number of tiny, low cost and low power sensor nodes to monitor some physical phenomenon. The major limitation in these networks is the use of non-rechargeable battery having limited power supply. The main cause of energy consumption in such networks is communication subsystem. This paper presents an energy efficient Cluster Cooperative Caching at Sensor (C3S) based upon grid type clustering. Sensor nodes belonging to the same cluster/grid form a cooperative cache system for the node since the cost for communication with them is low both in terms of energy consumption and message exchanges. The proposed scheme uses cache admission control and utility based data replacement policy to ensure that more useful data is retained in the local cache of a node. Simulation results demonstrate that C3S scheme performs better in various performance metrics than NICoCa which is existing cooperative caching protocol for WSNs.

Keywords: Cooperative caching, cache replacement, admission control, WSN, clustering.

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960 Performance Analysis of Cluster Based Dual Tired Network Model with INTK Security Scheme in a Wireless Sensor Network

Authors: D. Satish Kumar, S. Karthik

Abstract:

A dual tiered network model is designed to overcome the problem of energy alert and fault tolerance. This model minimizes the delay time and overcome failure of links. Performance analysis of the dual tiered network model is studied in this paper where the CA and LS schemes are compared with DEO optimal. We then evaluate  the Integrated Network Topological Control and Key Management (INTK) Schemes, which was proposed to add security features of the wireless sensor networks. Clustering efficiency, level of protections, the time complexity is some of the parameters of INTK scheme that were analyzed. We then evaluate the Cluster based Energy Competent n-coverage scheme (CEC n-coverage scheme) to ensure area coverage for wireless sensor networks.

Keywords: CEC n-coverage scheme, Clustering efficiency, Dual tired network, Wireless sensor networks.

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